온라인에서 발생하는 혐오표현은 널리 알려진 사회적 문제입니다. 익명성 때문에 혐오의 강도가 오프라인에 비해 더욱 세고, 온라인 상에 기록되기 때문에 그 내용을 지지하는 집단만 있다면 쉽게 불특정다수에게 확산되어 피해의 강도가 증폭됩니다. 최근에 발생한 일련의 비극적인 사건들로 포털 사이트들은 연예 및 스포츠 뉴스의 댓글란을 폐쇄하는 조치를 취했지만 그 곳이 아니더라도 혐오 발언은 어딘가에서 계속 표출이 되고 있기 때문에 다소 아쉬울 수 있는 해결책입니다. 이 때문에 어떤 텍스트에 혐오발언이 담겨 있는지 아닌지를 검출하는 모델은 불필요한 곳에서의 혐오 확산 및 노출을 제어할 수 있다는 면에서도, 표현의 자유를 침해하지 않고도 혐오발언으로 인한 피해를 감소시킬 수 있기 때문에도 중요합니다. 하지만 좋은 혐오탐지 모델 개발을 위해서는 우선, 좋은 데이터셋이 필요합니다. 그래서 이번 발표에서는 데이터를 구축하기 위해 했던 고민과 삽질기, 그리고 완성된 데이터를 활용해서 학습한 혐오탐지 모델을 소개할 예정입니다. 발표를 통해 혐오발언에 대한 다양한 논의와 모델 개선을 위해 필요한 작업들에 대한 토의가 이루어지길 기대합니다.

1. -BEEP!

2. ,
BridgingthegapbetweenAIandsocialproblems
< >
T.M.I
,
UpstageAI( )
https://bit.ly/3l0vNzI

3. •
•
• ?
•
• ?
•
•
• ...
•

4. ,

5. Facebook
https://transparency.facebook.com/community-standards-enforcement#hate-speech

6. Facebook
https://venturebeat.com/2020/05/12/facebook-is-using-more-ai-to-detect-hate-speech/

7. NAVER
•
•
• 2.0
• AI
• AI
https://blog.naver.com/naver_diary/221815294149

8. NAVER
•
•
• 2.0
• AI
• AI
https://blog.naver.com/naver_diary/221815294149

9. NAVER
https://blog.naver.com/naver_diary/222005616849

10. NAVER
https://d2.naver.com/helloworld/7753273

12. ?
• < >
•
•
• ,
•
• ,
•

13. NAVERnews < >top30
• :2018.1 ~2020.2
• :23,700 10,403,368
https://entertain.naver.com/ranking#type=hit_total&date=2020-02-29

14. 10,000
1. 2
2. < > 20
3.
4.
, ,
5.
,

15. ?

16. ?

17. ?
.

18. ?

19. ?

20. ?

21. ?

22. ?
https://about.fb.com/news/2017/06/hard-questions-hate-speech/

23. ?
Facebook
https://www.facebook.com/communitystandards/hate_speech

24. ?
NAVER
• : ,
• : ,
• :
• :
• : / / /
• :
https://d2.naver.com/helloworld/7753273

25. ?
https://www.humanrights.go.kr/site/program/board/basicboard/view?menuid=001003001003004&searchcategory=
%EA%B8%B0%ED%83%80%EB%B0%9C%EA%B0%84%EC%9E%90%EB%A3%8C&pagesize=10&boardtypeid=17&boardid=7604691

26. ?
, & . (2017). . , 1-373.

29. https://www.notion.so/c1ecb7cc52d446cc93d928d172ef8442

30. • 9,341 *
• 10,000 659
•
• (Training):7,896
• (Validation):471
• (Test):974
* 2 , DeepNatural

32. ?

33. ( ) !
DearJihyungMoon:
OnbehalfoftheSocialNLP2020ProgramCommittee,
Iamdelightedtoinformyouthatthefollowingsubmissionhasbeenacceptedtoappear
attheconference
https://store.line.me/stickershop/product/10567421/ko

34. Github
https://github.com/kocohub/korean-hate-speech

35. https://github.com/inmoonlight/koco

36. https://www.kaggle.com/c/korean-hate-speech-detection

37. Baseline
https://www.kaggle.com/c/korean-hate-speech-detection/leaderboard

38. Baseline
https://www.kaggle.com/c/korean-hate-speech-detection/leaderboard

40. :

41. !
. .

42. !

44. =
0.147

45. :

46. :
1.
2.

47. :
1.
2.
0.274

48. ?

49. ?

50. •
•
è

51. •
•
•
•
è

52. !
BidirectionalEncoderRepresentationsfromTransformers
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

53. !
BERT
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

54. BERT
•
• , (task)
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

55. BERT
• (Pre-training) ?
•
• (task)
(NLP)
• (1) (2)
• 100
•
• (Pre-training) ,
(Finetuning)
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

56. BERT
• ?
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
http://jalammar.github.io/illustrated-bert/

57. BERT
• ?
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
http://jalammar.github.io/illustrated-bert/

58. BERT
• ?
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
http://jalammar.github.io/illustrated-bert/

59. BERT
• (context)
•
• [MASK] ?
•
•
•
•
• , vectorspace
•
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

60. BERT
•
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
BERT
http://jalammar.github.io/illustrated-bert/

61. BERT
•
Devlin, Jacob, et al. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." Proceedings of the 2019 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
BERT
http://jalammar.github.io/illustrated-bert/

62. BERT
1.
2. BERT
3.BERT

63. •
•
• class 3

64. BERT
• BERT
• BERT
• BERT ,
Python
..

65. BERT
• BERT
https://huggingface.co/modelshttps://github.com/inmoonlight/detox

66. BERT
•
https://github.com/inmoonlight/detox

67. BERT
• Batch
https://github.com/inmoonlight/detox

68. BERT
• ,
https://github.com/inmoonlight/detox

69. BERT
• !
https://github.com/inmoonlight/detox

70. BERT
• configuration
https://github.com/inmoonlight/detox

71. BERT
•
https://github.com/inmoonlight/detox

72. BERT
•
https://www.kaggle.com/c/korean-hate-speech-detection/leaderboard
!

74. •
• ?
• Termmatching
•
• huggingface transformers pytorch
• deeplearningframework
• < >
• àhttps://github.com/inmoonlight/detox

75. jihyung.moon@upstage.ai